Palmer Penguins

Modeling (logistic regression, k-nearest neighbors, decision tree, multiclass logistic regression) with cross validated accuracy

Notable topics: Modeling (logistic regression, k-nearest neighbors, decision tree, multiclass logistic regression) with cross validated accuracy

Recorded on: 2020-07-27

Timestamps by: Eric Fletcher

## Screencast

## Timestamps

Create a pivoted histogram plot to visualize the distribution of penguin metrics using `pivot_longer`

, `geom_histogram`

, and `facet_wrap`

Create a pivoted density plot to visualize the distribution of penguin metrics using `geom_density`

and `facet_wrap`

Create a pivoted boxplot plot to visualize the distribution of penguin metrics using `geom_boxplot`

and `facet_wrap`

Create a bar plot to show penguin species changed over time

Create a bar plot to show specie counts per island

Create a logistic regression model to predict if a penguin is Adelie or not using bill length with cross validaiton of metrics

Create second logistic regression model using 4 predictive metrics (bill length, bill depth, flipper length, body mass) and then compare the accuracy of both models

Create a k-nearest neighbor model and then compare accuracy against logistic regression models to see which has the highest cross validated accuracy

What is the accuracy of the testing holdout data on the k-nearest neighbor model?

Create a decision tree and then compare accuracy against the previous models to see which has the highest cross validated accuracy + how to extract a decision tree

Perform multi class regression using `multinom_reg`

Summary of screencast